Publications by authors named "B Madore"
Physics Informed Neural Networks for Estimation of Tissue Properties from Multi-echo Configuration State MRI.
Med Image Comput Comput Assist Interv
October 2024
This work investigates the use of configuration state imaging together with deep neural networks to develop quantitative MRI techniques for deployment in an interventional setting. A physics modeling technique for inhomogeneous fields and heterogeneous tissues is presented and used to evaluate the theoretical capability of neural networks to estimate parameter maps from configuration state signal data. All tested normalization strategies achieved similar performance in estimating and .
View Article and Find Full Text PDFCharacterizing dispersion in bovine liver using ARFI-based shear wave rheometry.
Biomed Phys Eng Express
August 2024
Dispersion presents both a challenge and a diagnostic opportunity in shear wave elastography (SWE).(SWR) is an inversion technique for processing SWE data acquired using an acoustic radiation force impulse (ARFI) excitation. The main advantage of SWR is that it can characterize the shear properties of homogeneous soft media over a wide frequency range.
View Article and Find Full Text PDFDue to limitations in current motion tracking technologies and increasing interest in alternative sensors for motion tracking both inside and outside the MRI system, in this study we share our preliminary experience with three alternative sensors utilizing diverse technologies and interactions with tissue to monitor motion of the body surface, respiratory-related motion of major organs, and non-respiratory motion of deep-seated organs. These consist of (1) a Pilot-Tone RF transmitter combined with deep learning algorithms for tracking liver motion, (2) a single-channel ultrasound transducer with deep learning for monitoring bladder motion, and (3) a 3D Time-of-Flight camera for observing the motion of the anterior torso surface. Additionally, we demonstrate the capability of these sensors to simultaneously capture motion data outside the MRI environment, which is particularly relevant for procedures like radiation therapy, where motion status could be related to previously characterized cyclical anatomical data.
View Article and Find Full Text PDFArticle Synopsis
- - The study aimed to examine the incidence and severity of pulmonary embolism (PE) in COVID-19 patients during different variant periods (ancestral strain, Alpha, Delta, and Omicron) to see if newer variants and vaccinations reduced these factors.
- - Researchers analyzed data from 720 COVID-19 patients who had a CT pulmonary angiogram within a specific timeframe, finding that PE diagnoses varied slightly across variant periods but not significantly.
- - The results showed that the incidence and location of PE (in various artery types) did not significantly differ between the ancestral strain and the variants, suggesting that the risk remained consistent despite the presence of newer variants.
Article Synopsis
- The study aimed to explore the link between the severity of pneumonia seen on CT scans within six weeks of a COVID-19 diagnosis and the later emergence of lung abnormalities, known as post-COVID-19 lung abnormalities (Co-LA).
- Researchers assessed 132 COVID-19 patients, finding that 32% developed Co-LA 6 to 24 months later, with a significant correlation between the severity of initial pneumonia and the likelihood of developing these lung issues—70% of those with extensive pneumonia progressed to Co-LA compared to just 17% with non-extensive pneumonia and none with no pneumonia.
- The study concluded that greater pneumonia severity upon diagnosis increases the risk of developing long-term